Scheduling jobs and preventive maintenance on fuzzy job shop using genetic algorithm

Author

Zheng, You-Lian ; Li, Yuan-Xiang ; Lei, De-Ming

Author_Institution

State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China

Volume

3

fYear

2010

fDate

11-14 July 2010

Firstpage

1583

Lastpage

1589

Abstract

Preventive maintenance (PM) has been considered on many scheduling problems, however, the problem of scheduling jobs and PM on fuzzy job shop are seldom investigated. This paper presents a random key genetic algorithm (RKGA) for the problem with resumable jobs and PM in the fixed time intervals. RKGA uses a novel random key representation, a new decoding strategy incorporating maintenance operation, and discrete crossover. RKGA is applied to some instances to minimize the maximum fuzzy completion time. Computational results show the optimization ability of RKGA on fuzzy scheduling with PM.

Keywords

fuzzy set theory; genetic algorithms; job shop scheduling; preventive maintenance; decoding strategy; discrete crossover; fixed time intervals; fuzzy job shop; fuzzy scheduling; job scheduling; maintenance operation; maximum fuzzy completion time; preventive maintenance; random key genetic algorithm; random key representation; Biological cells; Cybernetics; Decoding; Job shop scheduling; Machine learning; Maintenance engineering; Processor scheduling; Fuzzy job shop scheduling; Genetic algorithm; Preventive maintenance; Random key;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics (ICMLC), 2010 International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-6526-2

Type

conf

DOI

10.1109/ICMLC.2010.5580802

Filename

5580802